메뉴 건너뛰기




Volumn 22, Issue 6, 2009, Pages 477-481

Semi-supervised fuzzy clustering: A kernel-based approach

Author keywords

Deflection; Kernel parameter; Optimization; Semi supervised clustering

Indexed keywords

CLASSIFICATION AND CLUSTERING; CLASSIFICATION ERRORS; CLUSTERING ACCURACY; CLUSTERING RESULTS; DEFLECTION; FUNCTION TRANSFORMATION; FUZZY C-MEAN ALGORITHM; FUZZY C-MEANS ALGORITHMS; FUZZY MEMBERSHIP; GLOBAL OPTIMUM; KERNEL BASED APPROACH; KERNEL BASED METHODS; KERNEL PARAMETER; LABELED DATA; LOCAL MINIMUMS; LOCAL OPTIMA; OBJECTIVE FUNCTIONS; REAL DATA SETS; SEMI-SUPERVISED; SEMI-SUPERVISED CLUSTERING; UNLABELED DATA;

EID: 67650474083     PISSN: 09507051     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.knosys.2009.06.009     Document Type: Article
Times cited : (62)

References (22)
  • 1
    • 33750738734 scopus 로고    scopus 로고
    • Co-training and expansion: Towards bridging theory and practice
    • L.K. Sawl, Y. Weiss, L. Bottou Eds, MIT Press, Cambridge, MA
    • M.-F. Balcan, A. Blum, K. Yang, Co-training and expansion: towards bridging theory and practice, in: L.K. Sawl, Y. Weiss, L. Bottou (Eds.), Advances in Neural Information Processing Systems, vol. 17, MIT Press, Cambridge, MA.
    • Advances in Neural Information Processing Systems , vol.17
    • Balcan, M.-F.1    Blum, A.2    Yang, K.3
  • 2
    • 0030150519 scopus 로고    scopus 로고
    • Partially supervised clustering for image segmentation
    • Bensaid A.M. Partially supervised clustering for image segmentation. Pattern Recognition 29 (1996) 859-871
    • (1996) Pattern Recognition , vol.29 , pp. 859-871
    • Bensaid, A.M.1
  • 5
    • 33646589004 scopus 로고    scopus 로고
    • Enhancement of fuzzy clustering by mechanisms of partial supervision
    • Bouchachiaa A., and Pedryczb W. Enhancement of fuzzy clustering by mechanisms of partial supervision. Fuzzy Sets and Systems 157 (2006) 1733-1759
    • (2006) Fuzzy Sets and Systems , vol.157 , pp. 1733-1759
    • Bouchachiaa, A.1    Pedryczb, W.2
  • 6
    • 0036825821 scopus 로고    scopus 로고
    • Kernel methods: a survey of current techniques
    • Campbell C. Kernel methods: a survey of current techniques. Neurocomputing 48 (2002) 63-84
    • (2002) Neurocomputing , vol.48 , pp. 63-84
    • Campbell, C.1
  • 8
    • 38849204864 scopus 로고    scopus 로고
    • Optimizing the data-dependent kernel under a unified kernel optimization framework
    • Chen B., Liu H.-w., and Bao Z. Optimizing the data-dependent kernel under a unified kernel optimization framework. Pattern Recognition 41 (2008) 2107-2119
    • (2008) Pattern Recognition , vol.41 , pp. 2107-2119
    • Chen, B.1    Liu, H.-w.2    Bao, Z.3
  • 10
    • 0036565280 scopus 로고    scopus 로고
    • Mercer kernel-based clustering in feature space
    • Girolami M. Mercer kernel-based clustering in feature space. IEEE Transactions on Neural Networks 13 3 (2002) 780-784
    • (2002) IEEE Transactions on Neural Networks , vol.13 , Issue.3 , pp. 780-784
    • Girolami, M.1
  • 11
    • 33745400518 scopus 로고    scopus 로고
    • Feature-based approach to semi-supervised similarity learning
    • Gosselin P.H., and Cord M. Feature-based approach to semi-supervised similarity learning. Pattern Recognition 39 (2006) 1839-1851
    • (2006) Pattern Recognition , vol.39 , pp. 1839-1851
    • Gosselin, P.H.1    Cord, M.2
  • 13
    • 0001938951 scopus 로고    scopus 로고
    • Transductive inference for text classification using support vector machines
    • Morgan Kaufmann, San Francisco, CA
    • T. Joachims, Transductive inference for text classification using support vector machines, in: 16th International Conference on Machine Learning, Morgan Kaufmann, San Francisco, CA, 1999, pp. 200-209.
    • (1999) 16th International Conference on Machine Learning , pp. 200-209
    • Joachims, T.1
  • 14
    • 10644261327 scopus 로고    scopus 로고
    • Evaluation of the performance of clustering algorithm in kernel-induced feature space
    • Kim D.-W., Lee K.-Y., Lee D., and Lee K.-H. Evaluation of the performance of clustering algorithm in kernel-induced feature space. Pattern Recognition 38 (2005) 607-611
    • (2005) Pattern Recognition , vol.38 , pp. 607-611
    • Kim, D.-W.1    Lee, K.-Y.2    Lee, D.3    Lee, K.-H.4
  • 17
    • 0033886806 scopus 로고    scopus 로고
    • Text classification from labeled and unlabeled documents using EM
    • Nigam K., McCallum A.K., Trun S., and Mitchell T. Text classification from labeled and unlabeled documents using EM. Machine Learning 39 2/3 (2000) 103-134
    • (2000) Machine Learning , vol.39 , Issue.2-3 , pp. 103-134
    • Nigam, K.1    McCallum, A.K.2    Trun, S.3    Mitchell, T.4
  • 19
    • 84911153095 scopus 로고    scopus 로고
    • Learning kernel parameters by using class separability measure
    • Canada
    • L. Wang, K.L. Chan, Learning kernel parameters by using class separability measure, in: NIPS'02 Workshop on Kernel Machines, Canada, 2002.
    • (2002) NIPS'02 Workshop on Kernel Machines
    • Wang, L.1    Chan, K.L.2
  • 21
    • 27344455216 scopus 로고    scopus 로고
    • Learning the kernel parameters in kernel minimum distance
    • Zhang D.-q., Chen S.-c., and Zhou Z.-h. Learning the kernel parameters in kernel minimum distance. Pattern Recognition 39 1 (2006) 133-135
    • (2006) Pattern Recognition , vol.39 , Issue.1 , pp. 133-135
    • Zhang, D.-q.1    Chen, S.-c.2    Zhou, Z.-h.3


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.